Scholar
Kushin Mukherjee
Google Scholar ID: MSVqlWEAAAAJ
Stanford University
Citations & Impact
Citations
307
H-index
7
i10-index
5
Publications
20
Co-authors
30
list available
Publications
Resume (English only)
Academic Achievements
- Paper 'AI-enhanced semantic feature norms for 786 concepts' accepted to both the BiAlign Workshop at ICLR, where it won the Best Paper Award, and to CogSci 2025, where it won the Computational Modeling Prize in Applied Cognition; paper 'SEVA: Leveraging sketches to evaluate alignment between human and machine visual abstraction' accepted to the NeurIPS Datasets and Benchmarks track; two papers accepted to the ICLR 2024 Workshop on Representational Alignment.
Research Experience
- Postdoctoral scholar in the Cognitive Tools Lab at Stanford University; interned at Apple AIML working on chart understanding in vision-language models; Kohler Fellow at the Wisconsin Institute for Discovery; collaborated with members of the Social Interaction Lab (SoIL) at Stanford, the Visual Intelligence and Technological Advances Lab at York, and the Neuroscience of Cognitive Control Lab at Princeton.
Education
- PhD in Psychology from UW-Madison, based in the Knowledge and Concepts Lab and the Schloss Visual Reasoning Lab; BA in Cognitive Science and Japanese from Vassar College, advised by Ken Livingston and Josh de Leeuw.
Background
- Broadly interested in the human ability to use and understand visualizations (charts, graphs, drawings) in service of communication and discovery. Focuses on developing computational cognitive models of visualization understanding to both better characterize human cognition and bridge the gap between modern AI systems and human-like understanding of visual concepts.
Miscellany
- Interested in how science and art can intersect to give rise to new ideas; was a CSLI intern at the Computation and Cognition Lab at Stanford, working with Judy Fan and Robert Hawkins.
